Paul Bruemmer

AI for Business

Start with the business problem. Then decide where AI belongs.

I help business owners identify useful applications of AI, evaluate the trade-offs and test a practical way forward. That might mean improving a workflow, supporting a team or developing a small prototype to answer a specific question.

The starting point is simple: define the desired outcome—and how you’ll measure success—before choosing tools.

01 — Opportunities

Where AI might help

These are opportunities to evaluate, not automatic recommendations. Whether any of them fits depends on your workflow, your customers and what you can measure.

  • Organizing information so the right people can find and use it quickly.
  • Intake and follow-up — making sure inquiries are captured, prioritized and routed.
  • Research support that gathers and summarizes while a person makes the call.
  • Repetitive work that consumes time better spent with customers.

02 — Method

Test usefulness before scaling

  1. 01Understand the workflow as it actually operates today.
  2. 02Establish a baseline — time, cost, quality — before anything changes.
  3. 03Run a bounded test with a narrow scope and clear limits.
  4. 04Review quality and effort honestly against the baseline.
  5. 05Expand, revise, or stop — based on what the test showed.

The goal isn’t to prove an idea is good. It’s to find out quickly and inexpensively whether it deserves more investment.

03 — Principles

Practical AI.Human judgment.Shared benefit.

I help businesses use AI thoughtfully—to save time, strengthen their teams, and serve customers better. My consulting combines business strategy with practical testing, clear limits, and human accountability, while respecting privacy and the knowledge people contribute.

My aim is to contribute to an AI future that expands human capability, preserves meaningful choice, and shares benefits broadly. Through each project, I strive to make responsible AI adoption a practical part of everyday business.

In practice that means human review of consequential outputs, respect for privacy and approved inputs, clear limits on what a system is allowed to do, accountability that stays with people, and a plan for handling errors.

04 — Selected work

Selected work—and what it demonstrates

AI Call Triage & Lead Capture

CatchDesk

Contractors miss calls while on jobs, and missed calls are missed work. CatchDesk is a bilingual AI system that captures, prioritizes and routes incoming opportunities — an example of starting with a concrete workflow problem and testing whether AI can carry a specific part of it.

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AI-Assisted Claim Verification

FACT — FactCheckWeekly

An evidence-first workflow for journalists that moves claims from submission through private verification, sourcing and editorial publication decisions — an example of AI assisting research while people keep editorial accountability.

View product

These are working explorations of specific problems, not claims of commercial outcomes. Further experiments and product work are summarized on the About page.

05 — Working together

How we can work together

  • Scoped advisory on where AI is — and isn’t — worth pursuing.
  • Fractional guidance alongside your existing team, agency or a complementary specialist.
  • Selective hands-on testing and prototyping when building something is the useful next step.

My background in search has kept me focused on how people find information, how systems interpret it, and whether the result is useful. I bring that same discipline to AI adoption.